Continuous-time stochastic volatility models are becoming increasingly popular in finance because of their flexibility in accommodating most stylized facts of financial time series. However, their estimation is difficult because the likelihood function does not have a closed-form expression. In...

We provide a simulation procedure for obtaining discretely observed values of Ornstein-Uhlenbeck processes with given (self-decomposable) marginal distribution. The method proposed, based on inversion of the characteristic function, completely circumvent problems encountered when trying to...

We propose a stochastic model for the probability of default based on diffusions with given marginal distribution and autocorrelation function. The model tries to capture stylized features observed in historical default rates and is analytically tractable. Estimation procedures and expressions...

Continuous non-Gaussian stationary processes of the OU-type are becoming increasingly popular given their flexibility in modelling stylized features of financial series such as asymmetry, heavy tails and jumps. The use of non-Gaussian marginal distributions makes likelihood analysis of these...

Questo studio prende l'avvio da un'iniziativa di ricerca il cui obiettivo consisteva nella costruzione di un indice sintetico di dipendenza dell'anziano dalla struttura in cui è ospitato, veloce da calcolare e a basso costo. La variabile fondamentale usata nell'analisi è la quantità di tempo...

This paper reviews a class of multifractal models obtained via products of exponential Ornstein–Uhlenbeck processes driven by Lévy motion. Given a self-decomposable distribution, conditions for constructing multifractal scenarios and general formulas for their Renyi functions are provided....